摘要:目的:探討表達吲哚胺2,3二氧化酶(IDO)的KC對同種異體小鼠移植皮片存活時間的影響及其機制。方法:構建BABL/c →C57BL/6的皮膚移植模型,分別于移植術后第2、7、14天輸注KC,于移植術后第7天每組各取2只皮瓣行HE染色和TUNEL以檢測淋巴細胞浸潤和凋亡情況。KaplanMeier對數秩檢驗對各組進行生存分析。結果:輸入表達IDO和FasL的KC能明顯延長BABL/c →C57BL/6皮膚移植模型中皮膚移植物的存活時間,1－甲基色氨酸能阻斷此效應。IFNγ組皮瓣浸潤淋巴細胞的凋亡率較高(Plt;0.05)。結論:表達IDO和FasL的KC在體內能明顯延長同種異體小鼠皮片的存活時間,IDO在KC維持外周免疫耐受中發揮重要作用。Abstract: Objective: To investigate kupffer cells(KC) expressing indoleamine 2,3dioxygenase(IDO) on the survival of grafted skin in mouse and its underlying mechanism. Methods: BABL/c skin was transplanted to C57BL/6. Donor KC were injected i.v. at days 2,7, 14 before transplantation. HE and TUNELAP were used to identify infiltrating cells and apoptotic cells in section of skin allografts from 7 days posttransplantation respectively. The survival rate of recipients among groups were analyzed by Logrank test. Results: Injection of KC expressing IDO and FasL from BABL/c mice into C57BL/6 could prolong a skin graft survival from the donor, but 1methyltryptophan could block the effect in vivo. The apoptosis rate of lymphocyte among skin graft in IFNγ group is more than other group(Plt;0.05). Conclusion: IDO and FasLexpressing KC from the donor of mouse can significantly prolong the skin graft survival. IDO may play an important role in KC to induce immune tolerance.
As one of the model medicinal plants for exploration of biochemical pathways and molecular biological questions on complex metabolic pathways, Catharanthus roseus synthesizes more than 100 terpenoid indole alkaloids (TIAs) used for clinical treatment of various diseases and for new drug discovery. Given that extensive studies have revealed the major metabolic pathways and the spatial-temporal biosynthesis of TIA in C. roseus plant, little is known about subcellular and inter-cellular trafficking or long-distance transport of TIA end products or intermediates, as well as their regulation. While these transport processes are indispensable for multi-organelle, -tissue and -cell biosynthesis, storage and their functions, great efforts have been made to explore these dynamic cellular processes. Progress has been made in past decades on transcriptional regulation of TIA biosynthesis by transcription factors as either activators or repressors; recent studies also revealed several transporters involved in subcellular and inter-cellular TIA trafficking. However, many details and the regulatory network for controlling the tissue-or cell-specific biosynthesis, transport and storage of serpentine and ajmalicine in root, catharanthine in leaf and root, vindoline specifically in leaf and vinblastine and vincristine only in green leaf and their biosynthetic intermediates remain to be determined. This review is to summarize the progress made in biosynthesis, transcriptional regulation and transport of TIAs. Based on analysis of organelle, tissue and cell-type specific biosynthesis and progresses in transport and trafficking of similar natural products, the transporters that might be involved in transport of TIAs and their synthetic intermediates are discussed; according to transcriptome analysis and bioinformatic approaches, the transcription factors that might be involved in TIA biosynthesis are analyzed. Further discussion is made on a broad context of transcriptional and transport regulation in order to guide our future research.
Background: With the increase in the amount of DNA methylation and gene expression data, the epigenetic mechanisms of cancers can be extensively investigate. Available methods integrate the DNA methylation and gene expression data into a network by specifying the anti-correlation between them. However, the correlation between methylation and expression is usually unknown and difficult to determine. Results: To address this issue, we present a novel multiple network framework for epigenetic modules, namely, Epigenetic Module based on Differential Networks (EMDN) algorithm, by simultaneously analyzing DNA methylation and gene expression data. The EMDN algorithm prevents the specification of the correlation between methylation and expression. The accuracy of EMDN algorithm is more efficient than that of modern approaches. On the basis of The Cancer Genome Atlas (TCGA) breast cancer data, we observe that the EMDN algorithm can recognize positively and negatively correlated modules and these modules are significantly more enriched in the known pathways than those obtained by other algorithms. These modules can serve as bio-markers to predict breast cancer subtypes by using methylation profiles, where positively and negatively correlated modules are of equal importance in the classification of cancer subtypes. Epigenetic modules also estimate the survival time of patients, and this factor is critical for cancer therapy. Conclusions: The proposed model and algorithm provide an effective method for the integrative analysis of DNA methylation and gene expression. The algorithm is freely available as an R-package at https://github.com/william0701/EMDN.